How much do data entry keyers make?

What the national Data Entry Keyers median says

The May 2025 BLS OEWS estimate puts the U.S. median for Data Entry Keyers at $41,340 per year. Median means the middle. Half of the wage values used for this estimate fall below that point. Half fall above it. The median is not one worker's pay. It is not a job offer. It is one clear mark for the middle of a broad national pay range.

BLS also lists 127,080 wage and salary jobs for Data Entry Keyers. That count covers jobs in the survey's scope. It does not count open job ads. It also leaves out people who work for themselves. The wage and job counts share the same May 2025 reference point, so they can be read together without mixing time periods.

The Data Entry Keyers mean of $43,310 per year is 4.8% above the $41,340 median on the same published median. Mean means BLS adds the wage values and divides the total by the number of jobs behind the estimate. A gap between mean and median shows that the shape is not even. It does not explain the cause of the gap.

The fields that make SOC 43-9021 its own page

BLS names this record Data Entry Keyers and gives it SOC 43-9021. The two-part code is the stable key for this page. A role with a close name keeps a different code, wage row, job count, and area pattern. WageScope never joins two SOC records because their words sound alike.

For SOC 43-9021, the U.S. row reports 127,080 wage and salary jobs. Its annual median is $41,340 per year. Its matching mean is $43,310 per year. These facts come from one national row and one May 2025 release.

SOC 43-9021 appears in 54 state or territory rows. It also has 301 metro rows and 105 nonmetro rows. A missing local row stays missing. We do not fill it with U.S. data or data for a similar job code.

• SOC 43-9021 10th percentile: $31,200 per year.
• SOC 43-9021 25th percentile: $35,760 per year.
• SOC 43-9021 median: $41,340 per year.
• SOC 43-9021 75th percentile: $48,410 per year.
• SOC 43-9021 90th percentile: $58,790 per year.
• SOC 43-9021 employment RSE: 2.1%. Mean-wage RSE: 0.5%.
• SOC 43-9021 has no national suppression mark in the fields shown on this page.

Read the Data Entry Keyers wage ladder from low to high

The 10th percentile is $31,200 per year. The 25th percentile is $35,760 per year. The median is $41,340 per year. The 75th percentile is $48,410 per year. The 90th percentile is $58,790 per year. Each point marks a place in the same national wage spread.

A percentile is a rank point. It is not a career step. For example, the 10th percentile means 10% of wage values are at or below that mark. It does not mean a new worker starts there. The 90th percentile means 90% are at or below that mark. It does not mean a worker can reach it after a set number of years.

The middle half runs from $35,760 to $48,410 per year. That span is $12,650. The full 10th-to-90th span is $27,590. These spans show why one median cannot stand in for every Data Entry Keyers job.

What the gaps around the Data Entry Keyers median show

The median is 32.5% above the 10th percentile. The 90th percentile is 42.2% above the median. The two sides do not have to match. A wider upper side can pull the mean up. A wider lower side can pull it down. The data shows the shape, but not the reason for that shape.

The 25th-to-median step is $5,580 per year. The median-to-75th step is $7,070 per year. These two steps give a closer look at the middle half. They are often more useful than a single top-to-bottom gap because they keep the center in view.

Use this ladder as a fact check when you read a job post. A posted range can sit below, near, or above these BLS marks. That does not make the post wrong. A job may differ by place, hours, level, field, employer, or work rules. Keep the posted range tied to that listing. Keep the BLS range tied to the whole occupation.

Metro areas with the highest published Data Entry Keyers medians

WageScope found 299 metro rows with the same published annual median for Data Entry Keyers. It sorts only those rows. It does not fill a blank row. It does not turn a blank into zero. The first six rows below have the highest published medians in this release. The list is a wage rank, not a rank of places to live or work.

The first row is San Jose-Sunnyvale-Santa Clara, CA, at $54,510 per year. The middle metro row by published pay is Oklahoma City, OK, at $39,540 per year. That middle metro mark gives one more check on how far the top rows sit from a common place in the set.

These are nominal wages. Nominal means the dollar amount shown in the source. This list does not adjust for local price levels. It also does not tell us how many openings an area has now. Use a local page to see price-level context when an exact BEA row exists. Use the separate job block to inspect current employer-title matches.

• 1. San Jose-Sunnyvale-Santa Clara, CA has a Data Entry Keyers median of $54,510 per year, or $13,170 above the U.S. Data Entry Keyers median. BLS lists 720 jobs there, against 127,080 across the U.S. The local location quotient is 0.77.
• 2. Albuquerque, NM has a Data Entry Keyers median of $53,320 per year, or $11,980 above the U.S. Data Entry Keyers median. BLS lists 220 jobs there, against 127,080 across the U.S. The local location quotient is 0.67.
• 3. Bismarck, ND has a Data Entry Keyers median of $53,140 per year, or $11,800 above the U.S. Data Entry Keyers median. BLS lists 30 jobs there, against 127,080 across the U.S. The local location quotient is 0.57.
• 4. Bloomington, IN has a Data Entry Keyers median of $51,760 per year, or $10,420 above the U.S. Data Entry Keyers median. BLS lists 230 jobs there, against 127,080 across the U.S. The local location quotient is 3.87.
• 5. Olympia-Lacey-Tumwater, WA has a Data Entry Keyers median of $51,660 per year, or $10,320 above the U.S. Data Entry Keyers median. BLS lists 140 jobs there, against 127,080 across the U.S. The local location quotient is 1.31.
• 6. New Haven, CT has a Data Entry Keyers median of $51,340 per year, or $10,000 above the U.S. Data Entry Keyers median. BLS lists 140 jobs there, against 127,080 across the U.S. The local location quotient is 0.62.

Metro areas with the largest Data Entry Keyers job estimates

A large wage can appear in a small job market. A large job market can have a lower wage. That is why WageScope keeps pay and job count in separate views. The six rows below have the largest published employment estimates for Data Entry Keyers among metro rows in this release. Employment means the number of wage and salary jobs in scope. It does not mean open roles.

New York-Newark-Jersey City, NY-NJ has the largest listed metro estimate in this set, at 10,110 jobs. Its median is $45,350 per year. Compare that with San Jose-Sunnyvale-Santa Clara, CA, which leads the published median list. The leaders may match, or they may not. Each list answers a different question.

Job count can help you see the scale of a local labor market. It cannot show churn, new hiring, job quality, remote work, or the chance that one person will get hired. Current listings add a second view, but they are a dated sample of posts. WageScope never turns the listing count into a demand score.

• 1. New York-Newark-Jersey City, NY-NJ has 10,110 estimated Data Entry Keyers jobs. That is 8.0% of the U.S. estimate of 127,080 jobs. Its median is $45,350 per year, or $4,010 above the U.S. Data Entry Keyers median. Its location quotient is 1.3.
• 2. Los Angeles-Long Beach-Anaheim, CA has 5,900 estimated Data Entry Keyers jobs. That is 4.6% of the U.S. estimate of 127,080 jobs. Its median is $47,040 per year, or $5,700 above the U.S. Data Entry Keyers median. Its location quotient is 1.15.
• 3. Dallas-Fort Worth-Arlington, TX has 5,610 estimated Data Entry Keyers jobs. That is 4.4% of the U.S. estimate of 127,080 jobs. Its median is $43,110 per year, or $1,770 above the U.S. Data Entry Keyers median. Its location quotient is 1.7.
• 4. Houston-Pasadena-The Woodlands, TX has 4,430 estimated Data Entry Keyers jobs. That is 3.5% of the U.S. estimate of 127,080 jobs. Its median is $39,520 per year, or $1,820 below the U.S. Data Entry Keyers median. Its location quotient is 1.65.
• 5. Chicago-Naperville-Elgin, IL-IN has 4,270 estimated Data Entry Keyers jobs. That is 3.4% of the U.S. estimate of 127,080 jobs. Its median is $44,650 per year, or $3,310 above the U.S. Data Entry Keyers median. Its location quotient is 1.16.
• 6. Phoenix-Mesa-Chandler, AZ has 2,650 estimated Data Entry Keyers jobs. That is 2.1% of the U.S. estimate of 127,080 jobs. Its median is $44,160 per year, or $2,820 above the U.S. Data Entry Keyers median. Its location quotient is 1.37.

Where Data Entry Keyers has a larger share of local jobs

Location quotient is a share check. A value of 1 means the role has the same share of local jobs as it has across the nation. A value above 1 means the local share is larger. A value below 1 means the local share is smaller. It is not a count. It is not a wage. It does not say that a place is growing.

Laredo, TX has the highest published location quotient in this bounded metro set, at 4.08. The same row lists 360 jobs and a median of $30,360 per year. Reading all three values keeps a high share from being mistaken for a large market or high pay.

A small area can have a high location quotient because the role makes up a large part of a small local job base. A large area can have many workers and a lower quotient. Use the quotient to ask where the role is common in the mix. Use employment to ask how many jobs BLS estimated. Use the wage fields to ask what the published pay range looks like.

• 1. Laredo, TX has a Data Entry Keyers location quotient of 4.08. BLS lists 360 jobs and a median of $30,360 per year, or $10,980 below the U.S. Data Entry Keyers median. The U.S. job estimate is 127,080.
• 2. Bloomington, IN has a Data Entry Keyers location quotient of 3.87. BLS lists 230 jobs and a median of $51,760 per year, or $10,420 above the U.S. Data Entry Keyers median. The U.S. job estimate is 127,080.
• 3. Mayaguez, PR has a Data Entry Keyers location quotient of 3.4. BLS lists 140 jobs and a median of $23,420 per year, or $17,920 below the U.S. Data Entry Keyers median. The U.S. job estimate is 127,080.
• 4. Topeka, KS has a Data Entry Keyers location quotient of 3.14. BLS lists 300 jobs and a median of $36,760 per year, or $4,580 below the U.S. Data Entry Keyers median. The U.S. job estimate is 127,080.
• 5. Shreveport-Bossier City, LA has a Data Entry Keyers location quotient of 2.95. BLS lists 390 jobs and a median of $36,920 per year, or $4,420 below the U.S. Data Entry Keyers median. The U.S. job estimate is 127,080.
• 6. San Juan-Bayamon-Caguas, PR has a Data Entry Keyers location quotient of 2.6. BLS lists 1,470 jobs and a median of $24,340 per year, or $17,000 below the U.S. Data Entry Keyers median. The U.S. job estimate is 127,080.

How Data Entry Keyers sits in Office and Administrative Support

Data Entry Keyers is SOC 43-9021. BLS places it in the Office and Administrative Support major group. Among 54 detailed roles in that group with a published annual median, Data Entry Keyers ranks 46 of 54 by median. This is a pay rank inside one source family. It is not a rank of skill, value, status, or career fit.

The closest same-family medians help set a fair peer frame. They do not claim that the work is the same. Official SOC titles can cover different tasks and settings. WageScope uses the family only because BLS publishes that link. It does not infer a career move, a skill match, or a hiring path from the wage gap.

Use these peer rows to spot whether the $41,340 median sits near many family roles or far from them. Then open a role's own page before using its number. Each role has a different code, job count, wage spread, and place pattern. One family label does not erase those facts.

• 1. Office Machine Operators, Except Computer, SOC 43-9071, has a U.S. median of $40,960 per year. Its gap from Data Entry Keyers is $380 per year.
• 2. Telephone Operators, SOC 43-2021, has a U.S. median of $41,740 per year. Its gap from Data Entry Keyers is $400 per year.
• 3. Tellers, SOC 43-3071, has a U.S. median of $43,030 per year. Its gap from Data Entry Keyers is $1,690 per year.
• 4. Mail Clerks and Mail Machine Operators, Except Postal Service, SOC 43-9051, has a U.S. median of $39,280 per year. Its gap from Data Entry Keyers is $2,060 per year.
• 5. Couriers and Messengers, SOC 43-5021, has a U.S. median of $39,200 per year. Its gap from Data Entry Keyers is $2,140 per year.
• 6. File Clerks, SOC 43-4071, has a U.S. median of $43,600 per year. Its gap from Data Entry Keyers is $2,260 per year.

How much care to use with the Data Entry Keyers estimate

The relative standard error for the job count is 2.1%. For the mean wage it is 0.5%. This measure, called RSE, shows survey precision. A smaller RSE often means less uncertainty from the sample. It does not tell you whether one person's pay is right or wrong.

The employment RSE applies to the 127,080 job estimate. The mean-wage RSE applies to the published mean of $43,310 per year. These fields do not give a matching RSE for the median or each percentile. WageScope shows the fields BLS published and does not move one RSE to another measure.

Survey values can change when BLS changes its methods, sample, models, or source year. That is why we show May 2025 on this page. Before we use a new release, we check its files, rows, and pages. A changed number is only a correction if the source calls it one.

A simple way to compare Data Entry Keyers across places

First, compare the same wage metric. Use annual with annual or hourly with hourly. Next, check the source date. Keep May 2025 BLS rows together. Then read employment and location quotient beside pay. This stops a high median from standing in for market size or local share. Last, add BEA price-level context only when the exact place has an approved row.

A state, metro, and nonmetro area are not the same kind of map. Do not rank them in one list without saying so. WageScope groups like with like. It also keeps a national row as a broad bench mark. A local page can show the local row, its state row when that link is exact, and the U.S. row without blending them.

If a value is blank, keep it blank. If BLS marks a top code, read it as a lower bound. Do not fill a blank from a nearby place. Do not turn a wage gap into a claim about taxes, hours, benefits, work rules, or a household budget. Those facts are not in the OEWS row.

Move from Data Entry Keyers wage data to one real listing

The job block on this page uses a strict employer-title match for Data Entry Keyers. It may show fewer rows than the full MeritLog job search. That is on purpose. A false negative is safer here than a job card for a different role. Each card keeps its employer, place, source, and seen date. The cards do not change the BLS wage data.

Open one listing and read its own pay, work place, level, and needs. Compare its posted range with the BLS spread only as context. A posted range is set by an employer for one role. The BLS range is a survey view across many jobs. Neither source proves that a person is fit for the work.

When you tailor a résumé, use work facts you can back up. Do not turn $41,340 into a skill or result. Do not copy a BLS job count into your work history. MeritLog can help shape confirmed experience for a chosen listing. The wage page stays public and read only. It does not save a job or create a résumé on page load.

What this Data Entry Keyers page does not claim

This page does not say what one Data Entry Keyers worker earns. It does not promise that a job pays the median. It does not state a starting wage. It does not explain why the mean and median differ. It does not add benefits, tips, stock, bonus pay, taxes, or work hours unless BLS includes them in the published wage measure.

The page does not count people who work for themselves. It does not turn 127,080 into current openings. It does not read private MeritLog jobs or Career Memory. MeritLog does not use the page to build a private career profile. While public analytics are on, GA4, Ahrefs, and Meta may get this page's URL. Use Your Privacy Choices or Global Privacy Control to turn that off. The page does not send its text to a model.

The best use is narrow and clear. Read the May 2025 BLS wage range. Check how the role changes by place. Add the separate 2024 BEA price level when an exact row exists. Inspect a dated employer-title match. Then make a résumé choice from facts you have confirmed. Keep each source tied to the question it can answer.